The ARCHY code, and permafrost carbonlmwg/travis.pdf · pores are water or ice-filled H H. H = heater location; part of study is to ... A z-t profile of sample ARCHY simulation of

The ARCHY code, and permafrost carbon

Bryan Travis Los Alamos

Irena OssolaColumbia University/LANL

February 9, 2010NCAR, Boulder, CO

Hydrology - surface snow, water (hillslope runoff, river routing)

Ecology - plants

Climate - atmosphere, clouds

Precip(t) snow/rain

Runoff, hydrographs, bank stability

Active layer - microbes …, emissions

T(t), s.i., albedo

Outflow to oceans, sediment, fresh water

Extreme events, fires

subsurface energy and fluid flow, permafrost dynamics

Coupled Dynamics of Arctic Regions

evap

SPA

HRR

ARCHY

ARCHY/MAGHNUM model

1-D, 2-D, 3-D + time; Cartesian, cylindrical coordinates; integrated finite differences; MPI version this year

Two-phase flow; mass and energy conservation equations + Darcy’s Law; water (single phase), water + air/vapor (two phase coupled), ice, melting/thawing, latent heat

Variable properties (H2O eos, permeability, porosity, thermal properties, spatial and temporal variation, feedbacks)

Chemistry – one version coupled to PHREEQC; solute transport, precipitation/dissolution, feedback to porosity and permeability

Microbial kinetics module – multiple Monod, multiple species including aerobic and anaerobic; C-N cycles

Checks and tests

• Analytic solutions for some simple cases• Diffusion with phase change (Stefan problems)• Single phase flow – steady solutions, comparisons to

other codes for transient cases• Similarity solutions for 2-phase flow• Comparisons to other numerical solutions (e.g., Grimm

& McSween; McKenzie et al)• Comparisons to experiments (e.g., McGraw)• Predecessor codes (MAGHNUM, TRACRI, …) have

been used and tested for a variety of applications

Microbial Activity

Bacterial respiration can convert large amounts organic carbon in soil to carbon dioxide andmethane. Several variables drive the response of microbial activity. Emission levels are sensitive tosoil composition, temperature, moisture and nutrients (such as nitrates and phosphates) andmicrobial community make-up.

-Methanogens: Bacteria that produce methane under anaerobic conditions from the breakdown of organic carbon.

Reaction: CH3COOH --> (1-x) CH4 + (1-x) CO2 + 2x Man where dMan/dt = d4R2 - λanMan

-Aerobes: Bacteria that utilize oxygen to metabolize organic carbon

Reaction: CH3COOH + (2-x) O2 --> where dMae/dt = d2R1 - λaeM

(2-x) CO2 + (2-x) H2O + x Mae

-Methanotrophs: Bacteria that consume methane as their predominant source of carbon and energy.

Reaction: CH4 + (2-x) O2 --> (1-x) CO2 + (2-x) H2O + x Mt where dMt/dt = d5R3 - λtMt

Carbon: Aerobic: R1 = k1(T) Mae [O2/(Ko2 + O2)][C/(KC+C)]

Anaerobic: R2 = k2(T) Man [I/(I + O2)][C/(KIC+C)]

Methanotrophic: R3 = k3(T) Mt [O2/(Ko2 + O2)][CH4/(KCH4+CH4)]

CO2: dCO2/dt = aR1 + bR2 + c(b3R3)

CH4: dCH4/dt = b2R2 - b3R3

O2: dO2/dt = -a2R1 - d3R3

-The various coefficients in the equations are determined from stoichiometry and experimental data.

Consumption Rates

Arctic Distribution of Permafrost and Borehole MeasurementsCourtesy of : http://www.gtnp.org/location_e.html

Measurements of temperature and CH4 and TOC concentrations vs depth at a Siberian site. Inthe top soil, low water level leads to oxic conditions and a limited methane accumulation due totransformation of methane by methanotrophs. At greater depths, methane accumulates fromanaerobic microbe activity. We are using databases of In situ data to calibrate our model.

Data from: S. Liebner, K. Rublack, T. Stuehrmann, and D. Wagner, 2009. Diversity of Aerobic Methanotrophic Bacteria in a Permafrost Active Layer Soil of the Lena Delta, Siberia

Example model domain

30 m

10 m

Q = 60 mW/m2

Porosity and permeability assumed randomly distributed; pores are water or ice-filled

HH

H = heater location; part of study is to see how different heater configurations affect permafrost distribution

Initial T = -5 C

Heat transport, melting/thawing, fluid flow

Ice (l) and Temperature (r) distributions - August

A z-t profile of sample ARCHY simulation of microbial species activity(aerobes, anaerobes, methanotrophs) in spring to summer

Plans for Model

• Comparison to soil data (CO2, CH4 soil measurements, fluxes)

• Study interactions between physical and biological factors

• Couple to surface vegetation and roots model, e.g., SPA

• Sensitivity analysis – ranking of importance• Prediction of responses to climate changes